- 3% annualized return
- 3.5% annualized standard deviation
- 0.00 correlation with your existing investment
Asset B with an expected:
- -5% annualized return
- > 50% annualized standard deviation
- 0.00 correlation with your existing investment
Easy question right? Perhaps not.
Asset B may actually improve long-term returns and reduce risk at the portfolio level, whereas an investment in Asset A may just be a drag on performance. This post will walk through an example, outline the math behind the results, and hypothesize how an investor may want to think about this phenomenon. Going one step further, I will outline how this may, in part, explain the low volatility anomaly (one example being that low-volatility stocks have produced higher risk-adjusted returns than high-beta stocks in most markets studied).
- Asset A: which reverts monthly from negative to positive performance (-0.75%, +1.26%, -0.75%, +1.26%), compounding to a 3% annualized return at a 3.5% standard deviation; in the chart below this assumes price action of $100 to $99 to $100 to $99… but with an incremental 3% return built in.
- Asset B: which reverts monthly from negative to positive performance (-15.4%, +17.2%, -15.4%, +17.2%), compounding to a -5% annualized return at a 56.5% standard deviation; in the chart below this assumes price action of $100 to $85 to $100 to $85… but with an incremental -5% negative return built in.
Yet… despite the 8% annualized outperformance of asset class A vs B that compounded to a 100% gain in asset A and a 70% decline in asset B, the 90% stock / 10% allocation to asset B results in a combined portfolio with higher returns, a higher sharpe ratio, and a lower drawdown relative to an allocation to the positive returning asset A (the benefit of the allocation to asset A was the reduced standard deviation as that allocation reduced risk asset exposure by 10%).
What gives?
- A more balanced blend (i.e. a closer to 50/50 weighting) will provide a greater rebalancing bonus
- A higher standard deviation of either asset class will result in a greater rebalancing bonus as an investment gets “more bang for your buck”
- A smaller correlation (or negative correlation) will will result in a greater rebalancing bonus
- A larger difference in the standard deviation of the two asset classes will result in a greater rebalancing bonus
In the case of a higher volatility solution, bullets #2 and #4 both result in a higher rebalancing bonus and higher return (all else equal). In my example, the rebalancing bonus went from roughly 10 bps given a 10% allocation to asset A to 150 bps given a similar 10% allocation to asset B.
Asset A: RB = 90% x 10% [~15% x 3% (1-0) + (~15% – 3%)^2/2] = ~10 bps
Asset B: RB = 90% x 10% [~15% x 56% (1-0) + (~15% – 56%)^2/2] = ~150 bps
For one, it certainly makes the case for strategies more likely to provide diversification to an existing portfolio that have a higher level of expected volatility. In my opinion, the most obvious strategy that is largely under-allocated to is managed futures and a lesser extent to certain hedge fund styles and (until the last 10 years when everyone piled in)… commodities. I would also note that the return expectation for an allocation to a high volatility diversifier doesn’t even need to be above 0%, as traditional bonds which have low volatility (thus a rebalancing bonus closer to 0) have a real return expectation close to 0% at present time.
Another potential implication of the rebalancing bonus and benefit of higher volatility is this may partially explain the low volatility anomaly seen within asset classes, such as within stocks and bonds. When viewed in isolation, less volatile asset classes seem like an anomaly… why would stocks or bonds with lower volatility outperform? But, when viewed within a broader portfolio construct it makes sense that these lower volatility investments may need a higher expected return to draw in investors.
Using the rebalancing bonus formula and the following inputs which go back to the December 1990 inception of the S&P 500 High Beta and S&P 500 Low Volatility indices, we get the following rebalancing bonuses despite the higher correlation of the S&P 500 High Beta index with the S&P 500 index:
High Beta: RB = 50% x 10% [14.4% x 28.2% (1-0.89)) + (14.4% – 28.2%)^2/2] = 35 bps
Low Volatility: RB = 50% x 10% [14.4% x 11.0% (1-0.75)) + (14.4% – 11.0%)^2/2] = 11 bps
Pretty close to the 38 bps and 12 bp rebalancing bonus they provided in reality. In this instance, that 26 bp differential makes up ~25% of the excess performance a 50/50 S&P 500 / low volatility blend “should” have had before the bonus.
